Title: Evaluation and selection of suppliers in the supply chain using the extended group PROMETHEE I procedures
Authors: Mohammad Azadfallah
Addresses: SAIPAYADAK, SAIPA After Sales Services Organization, Business Studies and Development Office, Tehran, Iran
Abstract: The aim of this paper is to extend the preference ranking organisation method for enrichment evaluations (PROMETHEE I) method for decision-making problems when there is a group of decision makers. One of the advantages of the proposed method is capability of taking the incomparability's into account. Although there are some studies considering this aspect as an advantage, in the current literature, conflicting viewpoints and disagreements are being discussed. In this paper, this phenomenon is thought to be acceptable and should be considered. In this study, a supplier selection problem is treated as multiple attribute group decision making (MAGDM) problems. In order to have a solution in group decision making, first we used PROMETHEE I method to find the individual preference ordering, then by using the weights of decision makers (DMs), all individual partial-orders are aggregated into a collective pre-order. In addition, a new TOPSIS-based approach introduced to determine the importance of DMs. Furthermore, a numerical example in supplier selection context presented to illustrate the feasibility and practability of the proposed MAGDM model. Finally, a comparative analysis is performed and the proposed method seems to be more satisfactory than the group PROMETHEE II (and implicitly, GDSS-PROMETHEE) method for solving the decision problems. While, two best-ranked alternatives are incomparable and there is no clear evidence in favour of either of alternatives, conventional method (PROMETHEE II and implicitly GDSS-PROMETHEE) introduced only one of them as the best (optimal) alternative.
Keywords: multiple attribute group decision making; MAGDM; preference ranking organisation method for enrichment evaluations; PROMETHEE; TOPSIS; incomparability; supplier selection problem.
International Journal of Supply Chain and Operations Resilience, 2017 Vol.3 No.1, pp.56 - 76
Received: 20 Mar 2017
Accepted: 21 Apr 2017
Published online: 27 Sep 2017 *